To make the complex task easy to conduct, existing studies usually decompose the joint extraction into several basic modules or processing steps [1]}, [2]}.
As shown in Figure REF ,
according to the extraction procedure of triple elements, these approaches fall into two categories:
multi-module multi-step and multi-module one-step.
The first category utilizes different modules in the framework of cascading classification [3]}, [4]}, [5]}, [6]}, [7]}, [2]} or text generation [9]}, [10]}, [11]} to obtain entities and relations step-by-step.
Although promising, this kind of models suffers from the problem of cascading errors since mistakes in early steps may affect the prediction results of later steps.
The second category attempts to identify entities and relations separately, and then combine them into triples based on their latent correlations [12]}, [13]}, [14]}.
However, due to insufficient mutual constraints between entities and relations in the separate recognition process, such methods tend to produce redundant information, leading to errors when assembling triples [15]}.
